# Build a RAG knowledge assistant with Google Drive and OpenAI: n8n workflow

> Started by another system calling it, and works across Google Drive and Pinecone. It puts OpenAI behind a retrieval step, so answers are drawn from...

Source: https://millionrounds.com/workflow/build-a-rag-knowledge-assistant-with-google-drive-and-openai (Millionrounds; every figure on the page links to its filing or article)

[Automation library](https://millionrounds.com/workflows) · [AI assistants](https://millionrounds.com/workflows?category=AI+assistants#library)

# Build a RAG knowledge assistant with Google Drive and OpenAI

Started by another system calling it, and works across Google Drive and Pinecone. It puts OpenAI behind a retrieval step, so answers are drawn from documents you supply rather than from the model alone. 16 steps: a working afternoon to understand properly.

Medium Calls a model: OpenAI Retrieval

[Download free](https://millionrounds.com/login?next=%2Fapp%2Fworkflow%2Fbuild-a-rag-knowledge-assistant-with-google-drive-and-openai)

**16 steps** Medium: a working afternoon

**0** Branches: places the flow splits

**0** Loops or waits

**2** Services it connects to

## The flow

Starts it 3 Model 11 Logic 1 Service 1

The steps in the order they run, from what starts it.

- 1 **Drive File Watcher** Google Drive trigger *Starts it*
- 2 **Split Text into Chunks** Text Splitter Character Text Splitter *Model*
- 3 **Generate Embeddings (Ingest)** Embeddings Open Ai *Model*
- 4 **User Query Webhook** Webhook *Starts it*
- 5 **Primary LLM (Agent Brain)** Lm Chat Open Ai *Model*
- 6 **Conversation Memory Buffer** Memory Buffer Window *Model*
- 7 **Generate Embeddings (Query)** Embeddings Open Ai *Model*
- 8 **Secondary LLM (Retriever QA)** Lm Chat Open Ai *Model*
- 9 **Extract File Metadata** Set *Logic*
- 10 **Parse Document Content** Document Default Data Loader *Model*
- 11 **Ingest into Pinecone Vector DB** Vector Store Pinecone *Model*
- 12 **AI Agent** Agent *Model*
- 13 **Retrieve Vectors from Pinecone** Vector Store Pinecone *Model*
- 14 **Vector Search QA Tool** Tool Vector Store *Model*
- 15 **Download File from Drive** Google Drive *Service*
- 16 **Respond to Webhook** Respond To Webhook *Starts it*

## How it's built

- **Starts on:** Another system calling it
- **Steps:** 16
- **Size:** Medium: a working afternoon
- **Connects to:** Google Drive, Pinecone
- **Model:** OpenAI
- **Retrieval:** Answers are drawn from documents you supply, not from the model alone

## Questions

What does it need to run?

An n8n account, plus your own Google Drive and Pinecone accounts, and a key for OpenAI. You connect your own accounts after importing it; none are included.

What starts it?

It starts on another system calling it.

Does it use AI?

Yes. It calls OpenAI. Its answers draw on documents you give it, not on the model alone. Model calls are billed by the provider, not by n8n.

How long does it take to set up?

Plan an afternoon. 16 steps is enough that you should read each one before running it.

How do I import it?

Copy the workflow, open a new workflow in n8n and paste. The steps appear on the canvas, ready for your own accounts.

**Before you run it**

Nothing here has been tested by us. It is somebody's working automation, read and described from its own steps. Treat the connections it wants as a list of accounts it will touch, and read the 16 steps before you point it at anything that matters.

## Run it in n8n

- **Create your n8n account** Free to start. n8n is where the workflow runs. [Create an n8n account ↗](https://millionrounds.com/n8n)
- **Download the workflow** Free with a Millionrounds account. [Download free](https://millionrounds.com/login?next=%2Fapp%2Fworkflow%2Fbuild-a-rag-knowledge-assistant-with-google-drive-and-openai)
- **Paste it into n8n** Open a new workflow in n8n and paste. Then connect your own accounts.

Stored with the author's traces removed: canvas notes, instance identifiers, saved credential names and any live document they had left behind.

## Connects to

Each opens the other workflows that use it.

[Google Drive](https://millionrounds.com/workflows?service=Google+Drive#library)[Pinecone](https://millionrounds.com/workflows?service=Pinecone#library)

## Workflows like it

Also ai assistants, with the same services where possible, closest in size first.

- [**Automate CVE detection with Google Drive** 16 steps · calls a model · Google Drive](https://millionrounds.com/workflow/automate-cve-detection-with-google-drive)
- [**Build a Placetel RAG voice assistant with Google Drive** 16 steps · calls a model · Google Drive, Supabase vectors](https://millionrounds.com/workflow/build-a-placetel-rag-voice-assistant-with-google-drive)
- [**Bulletproof RAG starter – Google Drive to chatbot with OpenAI** 16 steps · calls a model · Google Drive, Qdrant](https://millionrounds.com/workflow/bulletproof-rag-starter-google-drive-to-chatbot-with-openai)
- [**Handle guest inquiries for multiple rentals** 16 steps · calls a model · Google Drive](https://millionrounds.com/workflow/handle-guest-inquiries-for-multiple-rentals)
- [**WhatsApp group chat with OpenAI and Google Drive** 16 steps · calls a model · Google Drive, Pinecone](https://millionrounds.com/workflow/whatsapp-group-chat-with-openai-and-google-drive)
- [**AI-powered Upwork cover letter generator – Pinecone, Groq** 15 steps · calls a model · Pinecone](https://millionrounds.com/workflow/ai-powered-upwork-cover-letter-generator-pinecone-groq)